Data Mining and Modeling

The proliferation of machine learning means that learned classifiers lie at the
core of many products across Google. However, questions in practice are rarely so
clean as to just to use an out of the box algorithm. A big challenge is in
developing metrics, designing experimental methodologies, and modeling the space to
create parsimonious representations that capture the fundamentals of the problem.
These problems cut across Google’s products and services, from designing
experiments for testing new auction algorithms; to developing automated metrics to
measure the quality of a road map.

Data mining lies at the heart of many of these questions, and the research done at
Google is at the forefront of the field. Whether it is finding more efficient
algorithms for working with massive data sets, developing privacy-preserving
methods for classification, or designing new machine learning approaches, our group
continues to push the boundary of what is possible.